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008-microsoft-deberta-v3-base-finetuned-yahoo-800_200

Text Classification
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deberta-v2
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+ ---
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+ license: mit
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+ base_model: microsoft/deberta-v3-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ - precision
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+ - recall
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+ model-index:
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+ - name: 008-microsoft-deberta-v3-base-finetuned-yahoo-800_200
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # 008-microsoft-deberta-v3-base-finetuned-yahoo-800_200
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1139
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+ - F1: 0.6463
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+ - Accuracy: 0.65
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+ - Precision: 0.6514
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+ - Recall: 0.65
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+ - System Ram Used: 4.2190
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+ - System Ram Total: 83.4807
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+ - Gpu Ram Allocated: 2.0914
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+ - Gpu Ram Cached: 24.6602
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+ - Gpu Ram Total: 39.5640
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+ - Gpu Utilization: 33
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+ - Disk Space Used: 31.6928
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+ - Disk Space Total: 78.1898
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | System Ram Used | System Ram Total | Gpu Ram Allocated | Gpu Ram Cached | Gpu Ram Total | Gpu Utilization | Disk Space Used | Disk Space Total |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:---------------:|:----------------:|:-----------------:|:--------------:|:-------------:|:---------------:|:---------------:|:----------------:|
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+ | 2.2992 | 0.52 | 13 | 2.3031 | 0.0182 | 0.1 | 0.01 | 0.1 | 3.9340 | 83.4807 | 2.0915 | 24.6484 | 39.5640 | 50 | 24.7853 | 78.1898 |
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+ | 2.3096 | 1.04 | 26 | 2.2984 | 0.0182 | 0.1 | 0.01 | 0.1 | 4.1195 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 29.6206 | 78.1898 |
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+ | 2.2906 | 1.56 | 39 | 2.2852 | 0.0648 | 0.145 | 0.0525 | 0.145 | 4.2050 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 51 | 29.6206 | 78.1898 |
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+ | 2.2723 | 2.08 | 52 | 2.2198 | 0.1283 | 0.225 | 0.1625 | 0.225 | 4.2165 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 31.6924 | 78.1898 |
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+ | 2.1387 | 2.6 | 65 | 2.0293 | 0.2580 | 0.335 | 0.2655 | 0.335 | 4.2218 | 83.4807 | 2.0916 | 24.6602 | 39.5640 | 56 | 31.6925 | 78.1898 |
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+ | 1.9534 | 3.12 | 78 | 1.8757 | 0.3730 | 0.4 | 0.4419 | 0.4 | 4.2092 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 41 | 31.6925 | 78.1898 |
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+ | 1.7689 | 3.64 | 91 | 1.7209 | 0.4443 | 0.48 | 0.5198 | 0.48 | 4.2303 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 46 | 31.6925 | 78.1898 |
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+ | 1.6052 | 4.16 | 104 | 1.6318 | 0.5044 | 0.525 | 0.5139 | 0.525 | 4.2297 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 45 | 31.6926 | 78.1898 |
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+ | 1.4606 | 4.68 | 117 | 1.4969 | 0.5539 | 0.575 | 0.5788 | 0.575 | 4.2315 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 47 | 31.6926 | 78.1898 |
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+ | 1.2963 | 5.2 | 130 | 1.3920 | 0.6037 | 0.61 | 0.6063 | 0.61 | 4.2420 | 83.4807 | 2.0916 | 24.6602 | 39.5640 | 43 | 31.6926 | 78.1898 |
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+ | 1.1948 | 5.72 | 143 | 1.3030 | 0.6251 | 0.63 | 0.6292 | 0.63 | 4.2687 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 48 | 31.6926 | 78.1898 |
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+ | 1.0248 | 6.24 | 156 | 1.2568 | 0.6184 | 0.625 | 0.6354 | 0.625 | 4.2596 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 50 | 31.6927 | 78.1898 |
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+ | 0.9509 | 6.76 | 169 | 1.1911 | 0.6448 | 0.65 | 0.6552 | 0.65 | 4.2625 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6927 | 78.1898 |
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+ | 0.9081 | 7.28 | 182 | 1.1784 | 0.6441 | 0.655 | 0.6450 | 0.655 | 4.1955 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 50 | 31.6927 | 78.1898 |
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+ | 0.7629 | 7.8 | 195 | 1.1354 | 0.6598 | 0.655 | 0.6737 | 0.655 | 4.1868 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6927 | 78.1898 |
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+ | 0.7348 | 8.32 | 208 | 1.1369 | 0.6430 | 0.65 | 0.6483 | 0.65 | 4.2168 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 31.6927 | 78.1898 |
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+ | 0.7443 | 8.84 | 221 | 1.1274 | 0.6531 | 0.66 | 0.6576 | 0.66 | 4.2273 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 51 | 31.6927 | 78.1898 |
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+ | 0.5945 | 9.36 | 234 | 1.1228 | 0.6640 | 0.67 | 0.6694 | 0.67 | 4.1791 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6928 | 78.1898 |
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+ | 0.6885 | 9.88 | 247 | 1.1145 | 0.6463 | 0.65 | 0.6514 | 0.65 | 4.1849 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 48 | 31.6928 | 78.1898 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3